Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
"I know what you did last summer": query logs and user privacy
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized click prediction in sponsored search
Proceedings of the third ACM international conference on Web search and data mining
The demographics of web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
All of Statistics: A Concise Course in Statistical Inference
All of Statistics: A Concise Course in Statistical Inference
Who uses web search for what: and how
Proceedings of the fourth ACM international conference on Web search and data mining
Inferring the demographics of search users: social data meets search queries
Proceedings of the 22nd international conference on World Wide Web
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In advertising and content relevancy prediction it is important to understand whether, over time, information that reaches one demographic group spreads to others. In this paper we analyze the query log of a large U.S. web search engine to determine whether the same queries are performed by different demographic groups at different times, particularly when there are query bursts. We obtain aggregate demographic features from user-provided registration information (gender, birth year, ZIP code), U.S. census data, and election results. Given certain queries, we examine trends (from high to low and vice versa) and changes in the statistical spread of the demographic features of users that issue the queries over time periods that include query bursts. Our analysis shows that for certain types of queries (movies and news) distinct demographic groups perform searches at different times, suggesting that information related to such queries flows between them. Queries of movie titles, for instance, tend to be issued first by young and then by older users, where a sudden jump in age occurs upon the movie's release. To the best of our knowledge, this is the first time this problem has been studied using search query logs.